Cloud Application Predictability through Integrated Load-Balancing and Service Time Control

TL;DR: This work describes the technique and provides evidence that it allows us to achieve higher performance in terms of emergency management and user experience, and develops a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary.

Abstract: Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes with other decisions happening at the infrastructure level, like load-balancing choices. Here, we reconcile the two approaches, developing a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary. The proposal is based on a sound control-theoretical approach. The design of the approach avoids the pitfalls of interfering control decisions. We describe the technique and provide evidence that it allows us to achieve higher performance in terms of emergency management and user experience.